[DesireCourse.Net] Udemy - Machine Learning, Data Science And Deep Learning With Python

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  • 2. Statistics and Probability Refresher, and Python Practice/9. [Activity] Advanced Visualization with Seaborn.mp4 147.81 MB
    6. More Data Mining and Machine Learning Techniques/2. [Activity] Using KNN to predict a rating for a movie.mp4 142.06 MB
    10. Deep Learning and Neural Networks/3. [Activity] Deep Learning in the Tensorflow Playground.srt 141.62 MB
    10. Deep Learning and Neural Networks/3. [Activity] Deep Learning in the Tensorflow Playground.mp4 141.58 MB
    8. Apache Spark Machine Learning on Big Data/8. Introduction to Decision Trees in Spark.mp4 134.02 MB
    5. Recommender Systems/5. [Activity] Making Movie Recommendations to People.mp4 132.55 MB
    6. More Data Mining and Machine Learning Techniques/6. Reinforcement Learning.mp4 132.26 MB
    7. Dealing with Real-World Data/4. [Activity] Cleaning web log data.mp4 129.38 MB
    2. Statistics and Probability Refresher, and Python Practice/8. [Activity] A Crash Course in matplotlib.mp4 129.35 MB
    10. Deep Learning and Neural Networks/18. The Ethics of Deep Learning.mp4 128.24 MB
    2. Statistics and Probability Refresher, and Python Practice/11. [Exercise] Conditional Probability.mp4 125.14 MB
    1. Getting Started/11. Introducing the Pandas Library [Optional].mp4 123.1 MB
    8. Apache Spark Machine Learning on Big Data/9. [Activity] K-Means Clustering in Spark.mp4 117.86 MB
    2. Statistics and Probability Refresher, and Python Practice/10. [Activity] Covariance and Correlation.mp4 116.74 MB
    10. Deep Learning and Neural Networks/15. [Activity] Transfer Learning.mp4 115.26 MB
    2. Statistics and Probability Refresher, and Python Practice/7. [Activity] Percentiles and Moments.mp4 114.04 MB
    8. Apache Spark Machine Learning on Big Data/4. [Activity] Installing Spark - Part 2.mp4 111.98 MB
    2. Statistics and Probability Refresher, and Python Practice/4. [Activity] Variation and Standard Deviation.mp4 110.86 MB
    6. More Data Mining and Machine Learning Techniques/4. [Activity] PCA Example with the Iris data set.mp4 109.73 MB
    10. Deep Learning and Neural Networks/8. [Activity] Using Tensorflow, Part 2.mp4 108.64 MB
    5. Recommender Systems/3. [Activity] Finding Movie Similarities.mp4 107.83 MB
    8. Apache Spark Machine Learning on Big Data/12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.mp4 105.68 MB
    6. More Data Mining and Machine Learning Techniques/5. Data Warehousing Overview ETL and ELT.mp4 103.33 MB
    8. Apache Spark Machine Learning on Big Data/11. [Activity] Searching Wikipedia with Spark.mp4 102.99 MB
    1. Getting Started/4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.mp4 102.76 MB
    7. Dealing with Real-World Data/2. [Activity] K-Fold Cross-Validation to avoid overfitting.mp4 102.34 MB
    3. Predictive Models/1. [Activity] Linear Regression.mp4 100.46 MB
    4. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.mp4 98.61 MB
    8. Apache Spark Machine Learning on Big Data/6. Spark and the Resilient Distributed Dataset (RDD).mp4 98.51 MB
    11. Final Project/2. Final project review.mp4 98.5 MB
    9. Experimental Design ML in the Real World/2. AB Testing Concepts.srt 97.49 MB
    9. Experimental Design ML in the Real World/2. AB Testing Concepts.mp4 97.49 MB
    1. Getting Started/5. [Activity] MAC Installing and Using Anaconda & Course Materials.mp4 96.53 MB
    9. Experimental Design ML in the Real World/6. AB Test Gotchas.mp4 96.1 MB
    4. Machine Learning with Python/12. [Activity] Decision Trees Predicting Hiring Decisions.mp4 95.95 MB
    5. Recommender Systems/4. [Activity] Improving the Results of Movie Similarities.mp4 94.86 MB
    10. Deep Learning and Neural Networks/11. Convolutional Neural Networks (CNN's).mp4 93.09 MB
    10. Deep Learning and Neural Networks/9. [Activity] Introducing Keras.mp4 92.05 MB
    8. Apache Spark Machine Learning on Big Data/5. Spark Introduction.mp4 89.86 MB
    4. Machine Learning with Python/4. [Activity] Implementing a Spam Classifier with Naive Bayes.mp4 89.09 MB
    10. Deep Learning and Neural Networks/10. [Activity] Using Keras to Predict Political Affiliations.mp4 88.2 MB
    4. Machine Learning with Python/11. Decision Trees Concepts.mp4 86.53 MB
    5. Recommender Systems/1. User-Based Collaborative Filtering.mp4 86.37 MB
    10. Deep Learning and Neural Networks/5. Introducing Tensorflow.mp4 86.27 MB
    5. Recommender Systems/6. [Exercise] Improve the recommender's results.mp4 84.23 MB
    8. Apache Spark Machine Learning on Big Data/3. [Activity] Installing Spark - Part 1.mp4 83.63 MB
    9. Experimental Design ML in the Real World/4. [Activity] Hands-on With T-Tests.srt 81.63 MB
    9. Experimental Design ML in the Real World/4. [Activity] Hands-on With T-Tests.mp4 81.62 MB
    10. Deep Learning and Neural Networks/14. [Activity] Using a RNN for sentiment analysis.mp4 81.36 MB
    1. Getting Started/6. [Activity] LINUX Installing and Using Anaconda & Course Materials.mp4 80.21 MB
    10. Deep Learning and Neural Networks/2. The History of Artificial Neural Networks.mp4 79.98 MB
    7. Dealing with Real-World Data/3. Data Cleaning and Normalization.mp4 78.75 MB
    6. More Data Mining and Machine Learning Techniques/7. [Activity] Reinforcement Learning & Q-Learning with Gym.mp4 77.96 MB
    2. Statistics and Probability Refresher, and Python Practice/1. Types of Data.mp4 77.25 MB
    2. Statistics and Probability Refresher, and Python Practice/6. Common Data Distributions.mp4 75.37 MB
    5. Recommender Systems/2. Item-Based Collaborative Filtering.mp4 75 MB
    10. Deep Learning and Neural Networks/1. Deep Learning Pre-Requisites.mp4 74.17 MB
    3. Predictive Models/3. [Activity] Multiple Regression, and Predicting Car Prices.mp4 73.85 MB
    10. Deep Learning and Neural Networks/7. [Activity] Using Tensorflow, Part 1.mp4 72.69 MB
    4. Machine Learning with Python/5. K-Means Clustering.mp4 71.94 MB
    10. Deep Learning and Neural Networks/12. [Activity] Using CNN's for handwriting recognition.mp4 69.56 MB
    10. Deep Learning and Neural Networks/13. Recurrent Neural Networks (RNN's).mp4 69.17 MB
    8. Apache Spark Machine Learning on Big Data/10. TF IDF.mp4 68.85 MB
    6. More Data Mining and Machine Learning Techniques/3. Dimensionality Reduction; Principal Component Analysis.mp4 67.74 MB
    3. Predictive Models/2. [Activity] Polynomial Regression.mp4 66.77 MB
    7. Dealing with Real-World Data/1. BiasVariance Tradeoff.mp4 66.31 MB
    4. Machine Learning with Python/13. Ensemble Learning.mp4 65.21 MB
    9. Experimental Design ML in the Real World/3. T-Tests and P-Values.mp4 64.92 MB
    10. Deep Learning and Neural Networks/4. Deep Learning Details.srt 64.25 MB
    10. Deep Learning and Neural Networks/4. Deep Learning Details.mp4 64.22 MB
    12. You made it!/1. More to Explore.mp4 64.06 MB
    2. Statistics and Probability Refresher, and Python Practice/3. [Activity] Using mean, median, and mode in Python.mp4 61.93 MB
    1. Getting Started/1. Introduction.mp4 59.6 MB
    2. Statistics and Probability Refresher, and Python Practice/13. Bayes' Theorem.mp4 58.9 MB
    4. Machine Learning with Python/2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4 58.14 MB
    4. Machine Learning with Python/6. [Activity] Clustering people based on income and age.mp4 57.29 MB
    2. Statistics and Probability Refresher, and Python Practice/2. Mean, Median, Mode.mp4 56.15 MB
    8. Apache Spark Machine Learning on Big Data/7. Introducing MLLib.mp4 54.74 MB
    11. Final Project/1. Your final project assignment.mp4 51.63 MB
    7. Dealing with Real-World Data/8. Imputation Techniques for Missing Data.mp4 49.02 MB
    7. Dealing with Real-World Data/10. Binning, Transforming, Encoding, Scaling, and Shuffling.mp4 47.91 MB
    3. Predictive Models/4. Multi-Level Models.mp4 47.47 MB
    4. Machine Learning with Python/14. Support Vector Machines (SVM) Overview.mp4 44.74 MB
    4. Machine Learning with Python/15. [Activity] Using SVM to cluster people using scikit-learn.mp4 43.94 MB
    7. Dealing with Real-World Data/7. Feature Engineering and the Curse of Dimensionality.mp4 41.71 MB
    4. Machine Learning with Python/3. Bayesian Methods Concepts.mp4 40.73 MB
    6. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.mp4 40.28 MB
    10. Deep Learning and Neural Networks/19. Learning More about Deep Learning.mp4 38.64 MB
    7. Dealing with Real-World Data/5. Normalizing numerical data.mp4 38.2 MB
    7. Dealing with Real-World Data/9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.mp4 36.34 MB
    7. Dealing with Real-World Data/6. [Activity] Detecting outliers.mp4 36.32 MB
    4. Machine Learning with Python/7. Measuring Entropy.mp4 34.97 MB
    9. Experimental Design ML in the Real World/5. Determining How Long to Run an Experiment.mp4 34.84 MB
    10. Deep Learning and Neural Networks/17. Deep Learning Regularization with Dropout and Early Stopping.mp4 33.64 MB
    9. Experimental Design ML in the Real World/1. Deploying Models to Real-Time Systems.mp4 33.04 MB
    1. Getting Started/7. Python Basics, Part 1 [Optional].mp4 32.98 MB
    2. Statistics and Probability Refresher, and Python Practice/5. Probability Density Function; Probability Mass Function.mp4 30.07 MB
    6. More Data Mining and Machine Learning Techniques/9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).mp4 25.79 MB
    2. Statistics and Probability Refresher, and Python Practice/12. Exercise Solution Conditional Probability of Purchase by Age.mp4 22 MB
    1. Getting Started/10. [Activity] Python Basics, Part 4 [Optional].mp4 21.12 MB
    1. Getting Started/8. [Activity] Python Basics, Part 2 [Optional].mp4 20.63 MB
    1. Getting Started/2. Udemy 101 Getting the Most From This Course.mp4 19.77 MB
    10. Deep Learning and Neural Networks/16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.mp4 18.43 MB
    6. More Data Mining and Machine Learning Techniques/8. Understanding a Confusion Matrix.mp4 14.84 MB
    4. Machine Learning with Python/9. [Activity] MAC Installing Graphviz.mp4 14.83 MB
    1. Getting Started/9. [Activity] Python Basics, Part 3 [Optional].mp4 10.09 MB
    4. Machine Learning with Python/10. [Activity] LINUX Installing Graphviz.mp4 7.05 MB
    4. Machine Learning with Python/8. [Activity] WINDOWS Installing Graphviz.mp4 2.06 MB
    2. Statistics and Probability Refresher, and Python Practice/9. [Activity] Advanced Visualization with Seaborn.srt 29.96 KB
    2. Statistics and Probability Refresher, and Python Practice/8. [Activity] A Crash Course in matplotlib.srt 28.57 KB
    6. More Data Mining and Machine Learning Techniques/6. Reinforcement Learning.srt 28.5 KB
    6. More Data Mining and Machine Learning Techniques/2. [Activity] Using KNN to predict a rating for a movie.srt 28.48 KB
    2. Statistics and Probability Refresher, and Python Practice/11. [Exercise] Conditional Probability.srt 28.41 KB
    2. Statistics and Probability Refresher, and Python Practice/7. [Activity] Percentiles and Moments.srt 28.33 KB
    8. Apache Spark Machine Learning on Big Data/8. Introduction to Decision Trees in Spark.srt 28.1 KB
    2. Statistics and Probability Refresher, and Python Practice/10. [Activity] Covariance and Correlation.srt 25.91 KB
    2. Statistics and Probability Refresher, and Python Practice/4. [Activity] Variation and Standard Deviation.srt 25.83 KB
    3. Predictive Models/1. [Activity] Linear Regression.srt 25.7 KB
    7. Dealing with Real-World Data/2. [Activity] K-Fold Cross-Validation to avoid overfitting.srt 24.54 KB
    11. Final Project/2. Final project review.srt 24.51 KB
    8. Apache Spark Machine Learning on Big Data/6. Spark and the Resilient Distributed Dataset (RDD).srt 24.41 KB
    7. Dealing with Real-World Data/4. [Activity] Cleaning web log data.srt 23.78 KB
    10. Deep Learning and Neural Networks/9. [Activity] Introducing Keras.srt 23.75 KB
    10. Deep Learning and Neural Networks/8. [Activity] Using Tensorflow, Part 2.srt 23.35 KB
    5. Recommender Systems/5. [Activity] Making Movie Recommendations to People.srt 22.61 KB
    10. Deep Learning and Neural Networks/5. Introducing Tensorflow.srt 22.51 KB
    6. More Data Mining and Machine Learning Techniques/7. [Activity] Reinforcement Learning & Q-Learning with Gym.srt 22.49 KB
    4. Machine Learning with Python/12. [Activity] Decision Trees Predicting Hiring Decisions.srt 22.45 KB
    9. Experimental Design ML in the Real World/6. AB Test Gotchas.srt 21.88 KB
    10. Deep Learning and Neural Networks/15. [Activity] Transfer Learning.srt 21.53 KB
    10. Deep Learning and Neural Networks/1. Deep Learning Pre-Requisites.srt 21.52 KB
    8. Apache Spark Machine Learning on Big Data/5. Spark Introduction.srt 21.21 KB
    6. More Data Mining and Machine Learning Techniques/4. [Activity] PCA Example with the Iris data set.srt 21.2 KB
    10. Deep Learning and Neural Networks/10. [Activity] Using Keras to Predict Political Affiliations.srt 21.14 KB
    3. Predictive Models/3. [Activity] Multiple Regression, and Predicting Car Prices.srt 21.13 KB
    4. Machine Learning with Python/11. Decision Trees Concepts.srt 21.1 KB
    4. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.srt 20.9 KB
    5. Recommender Systems/3. [Activity] Finding Movie Similarities.srt 20.08 KB
    5. Recommender Systems/2. Item-Based Collaborative Filtering.srt 19.99 KB
    10. Deep Learning and Neural Networks/11. Convolutional Neural Networks (CNN's).srt 19.86 KB
    10. Deep Learning and Neural Networks/18. The Ethics of Deep Learning.srt 19.84 KB
    6. More Data Mining and Machine Learning Techniques/5. Data Warehousing Overview ETL and ELT.srt 19.74 KB
    5. Recommender Systems/1. User-Based Collaborative Filtering.srt 19.38 KB
    10. Deep Learning and Neural Networks/2. The History of Artificial Neural Networks.srt 19.07 KB
    1. Getting Started/4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.srt 18.88 KB
    10. Deep Learning and Neural Networks/13. Recurrent Neural Networks (RNN's).srt 18.48 KB
    1. Getting Started/11. Introducing the Pandas Library [Optional].srt 18.05 KB
    8. Apache Spark Machine Learning on Big Data/9. [Activity] K-Means Clustering in Spark.srt 17.73 KB
    3. Predictive Models/2. [Activity] Polynomial Regression.srt 17.59 KB
    4. Machine Learning with Python/4. [Activity] Implementing a Spam Classifier with Naive Bayes.srt 17.42 KB
    4. Machine Learning with Python/5. K-Means Clustering.srt 17.2 KB
    7. Dealing with Real-World Data/3. Data Cleaning and Normalization.srt 17.08 KB
    10. Deep Learning and Neural Networks/14. [Activity] Using a RNN for sentiment analysis.srt 16.82 KB
    5. Recommender Systems/4. [Activity] Improving the Results of Movie Similarities.srt 16.78 KB
    2. Statistics and Probability Refresher, and Python Practice/1. Types of Data.srt 16.24 KB
    2. Statistics and Probability Refresher, and Python Practice/6. Common Data Distributions.srt 16.08 KB
    9. Experimental Design ML in the Real World/1. Deploying Models to Real-Time Systems.srt 15.42 KB
    2. Statistics and Probability Refresher, and Python Practice/3. [Activity] Using mean, median, and mode in Python.srt 15.01 KB
    4. Machine Learning with Python/15. [Activity] Using SVM to cluster people using scikit-learn.srt 14.85 KB
    1. Getting Started/6. [Activity] LINUX Installing and Using Anaconda & Course Materials.srt 14.66 KB
    4. Machine Learning with Python/13. Ensemble Learning.srt 14.55 KB
    1. Getting Started/5. [Activity] MAC Installing and Using Anaconda & Course Materials.srt 14.48 KB
    7. Dealing with Real-World Data/1. BiasVariance Tradeoff.srt 14.4 KB
    7. Dealing with Real-World Data/8. Imputation Techniques for Missing Data.srt 14.31 KB
    7. Dealing with Real-World Data/10. Binning, Transforming, Encoding, Scaling, and Shuffling.srt 14.21 KB
    8. Apache Spark Machine Learning on Big Data/10. TF IDF.srt 14.03 KB
    8. Apache Spark Machine Learning on Big Data/12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.srt 13.91 KB
    10. Deep Learning and Neural Networks/7. [Activity] Using Tensorflow, Part 1.srt 13.84 KB
    10. Deep Learning and Neural Networks/12. [Activity] Using CNN's for handwriting recognition.srt 13.76 KB
    5. Recommender Systems/6. [Exercise] Improve the recommender's results.srt 13.2 KB
    9. Experimental Design ML in the Real World/3. T-Tests and P-Values.srt 13.16 KB
    4. Machine Learning with Python/2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.srt 13.11 KB
    2. Statistics and Probability Refresher, and Python Practice/2. Mean, Median, Mode.srt 12.95 KB
    8. Apache Spark Machine Learning on Big Data/11. [Activity] Searching Wikipedia with Spark.srt 12.85 KB
    6. More Data Mining and Machine Learning Techniques/3. Dimensionality Reduction; Principal Component Analysis.srt 12.32 KB
    8. Apache Spark Machine Learning on Big Data/3. [Activity] Installing Spark - Part 1.srt 12.04 KB
    10. Deep Learning and Neural Networks/17. Deep Learning Regularization with Dropout and Early Stopping.srt 11.97 KB
    7. Dealing with Real-World Data/7. Feature Engineering and the Curse of Dimensionality.srt 11.83 KB
    11. Final Project/1. Your final project assignment.srt 11.56 KB
    4. Machine Learning with Python/6. [Activity] Clustering people based on income and age.srt 11.55 KB
    2. Statistics and Probability Refresher, and Python Practice/13. Bayes' Theorem.srt 11.49 KB
    8. Apache Spark Machine Learning on Big Data/7. Introducing MLLib.srt 11.46 KB
    7. Dealing with Real-World Data/6. [Activity] Detecting outliers.srt 11.44 KB
    6. More Data Mining and Machine Learning Techniques/9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).srt 10.82 KB
    3. Predictive Models/4. Multi-Level Models.srt 10.66 KB
    8. Apache Spark Machine Learning on Big Data/4. [Activity] Installing Spark - Part 2.srt 10.59 KB
    4. Machine Learning with Python/14. Support Vector Machines (SVM) Overview.srt 9.88 KB
    7. Dealing with Real-World Data/9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.srt 9.88 KB
    6. More Data Mining and Machine Learning Techniques/8. Understanding a Confusion Matrix.srt 9.71 KB
    6. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.srt 8.95 KB
    4. Machine Learning with Python/3. Bayesian Methods Concepts.srt 8.83 KB
    9. Experimental Design ML in the Real World/5. Determining How Long to Run an Experiment.srt 8.34 KB
    10. Deep Learning and Neural Networks/16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.srt 8.29 KB
    1. Getting Started/7. Python Basics, Part 1 [Optional].srt 7.76 KB
    7. Dealing with Real-World Data/5. Normalizing numerical data.srt 7.65 KB
    1. Getting Started/8. [Activity] Python Basics, Part 2 [Optional].srt 7.63 KB
    2. Statistics and Probability Refresher, and Python Practice/5. Probability Density Function; Probability Mass Function.srt 7.59 KB
    12. You made it!/3. Bonus Lecture More courses to explore!.html 7.32 KB
    12. You made it!/1. More to Explore.srt 7.24 KB
    4. Machine Learning with Python/7. Measuring Entropy.srt 6.9 KB
    1. Getting Started/10. [Activity] Python Basics, Part 4 [Optional].srt 6 KB
    1. Getting Started/1. Introduction.srt 4.75 KB
    1. Getting Started/9. [Activity] Python Basics, Part 3 [Optional].srt 4.24 KB
    1. Getting Started/2. Udemy 101 Getting the Most From This Course.srt 4.04 KB
    2. Statistics and Probability Refresher, and Python Practice/12. Exercise Solution Conditional Probability of Purchase by Age.srt 3.99 KB
    8. Apache Spark Machine Learning on Big Data/2. Spark installation notes for MacOS and Linux users.html 3.48 KB
    10. Deep Learning and Neural Networks/19. Learning More about Deep Learning.srt 3.14 KB
    4. Machine Learning with Python/9. [Activity] MAC Installing Graphviz.srt 1.26 KB
    4. Machine Learning with Python/10. [Activity] LINUX Installing Graphviz.srt 1.11 KB
    10. Deep Learning and Neural Networks/6. Important note about Tensorflow 2.html 1000 B
    4. Machine Learning with Python/8. [Activity] WINDOWS Installing Graphviz.srt 689 B
    8. Apache Spark Machine Learning on Big Data/1. Warning about Java 11 and Spark 2.4!.html 650 B
    12. You made it!/2. Don't Forget to Leave a Rating!.html 564 B
    1. Getting Started/3. Installation Getting Started.html 265 B
    6. More Data Mining and Machine Learning Techniques/6.2 Pac-Man Example.html 145 B
    6. More Data Mining and Machine Learning Techniques/6.1 Cat and Mouse Example.html 140 B
    6. More Data Mining and Machine Learning Techniques/6.3 Python Markov Decision Process Toolbox.html 119 B
    8. Apache Spark Machine Learning on Big Data/3.1 winutils.exe.html 108 B
    8. Apache Spark Machine Learning on Big Data/4.1 winutils.exe.html 108 B
    [DesireCourse.Net].url 51 B
    [CourseClub.Me].url 48 B

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